Buggy code:
public class KMeans extends ModelBuilder < KMeansModel , KMeansModel . KMeansParameters , KMeansModel . KMeansOutput > { @ Override public ModelCategory [ ] can_build ( ) { } public enum Initialization { Random , PlusPlus , Furthest , User ; } private int _ncats ; private final double TOLERANCE = 1.0E-6 ; public KMeans ( KMeansModel . KMeansParameters parms ) { } public ModelBuilderSchema schema ( ) { } @ Override public Job < KMeansModel > trainModel ( ) { } @ Override public void init ( boolean expensive ) { super . init ( expensive ) ; if ( ( ( _parms . _k ) < 1 ) || ( ( _parms . _k ) > 10000000 ) ) error ( "_k" , "k<seq2seq4repair_space>must<seq2seq4repair_space>be<seq2seq4repair_space>between<seq2seq4repair_space>1<seq2seq4repair_space>and<seq2seq4repair_space>1e7" ) ; if ( ( ( _parms . _max_iters ) < 0 ) || ( ( _parms . _max_iters ) > 1000000 ) ) error ( "_max_iters" , "<seq2seq4repair_space>max_iters<seq2seq4repair_space>must<seq2seq4repair_space>be<seq2seq4repair_space>between<seq2seq4repair_space>0<seq2seq4repair_space>and<seq2seq4repair_space>1e6" ) ; if ( ( _train ) == null ) return ; if ( ( _train . numRows ( ) ) < ( _parms . _k ) ) <START_BUG> error ( "_k" , ( ( ( ( "Cannot<seq2seq4repair_space>make<seq2seq4repair_space>" + ( _parms . _k ) ) + "<seq2seq4repair_space>clusters<seq2seq4repair_space>out<seq2seq4repair_space>of<seq2seq4repair_space>" ) + ( _train . numRows ( ) ) ) + "<seq2seq4repair_space>rows." ) ) ; <END_BUG> if ( null != ( _parms . _user_points ) ) { if ( ( _user_points . get ( ) . numCols ( ) ) != ( _train . numCols ( ) ) ) { error ( "_user_points" , ( ( "The<seq2seq4repair_space>user-specified<seq2seq4repair_space>points<seq2seq4repair_space>must<seq2seq4repair_space>have<seq2seq4repair_space>the<seq2seq4repair_space>same<seq2seq4repair_space>number<seq2seq4repair_space>of<seq2seq4repair_space>columns<seq2seq4repair_space>(" + ( _train . numCols ( ) ) ) + ")<seq2seq4repair_space>as<seq2seq4repair_space>the<seq2seq4repair_space>training<seq2seq4repair_space>observations" ) ) ; } } for ( Vec v : _train . vecs ( ) ) if ( v . isEnum ( ) ) ( _ncats ) ++ ; Vec [ ] vecs = _train . vecs ( ) ; int ncats = 0 ; int nvecs = vecs . length ; while ( ncats != nvecs ) { while ( ( ncats < nvecs ) && ( vecs [ ncats ] . isEnum ( ) ) ) ncats ++ ; while ( ( nvecs > 0 ) && ( ! ( vecs [ ( nvecs - 1 ) ] . isEnum ( ) ) ) ) nvecs -- ; if ( ncats < ( nvecs - 1 ) ) _train . swap ( ncats , ( nvecs - 1 ) ) ; } _ncats = ncats ; } private class KMeansDriver extends H2OCountedCompleter < KMeans . KMeansDriver > { double [ ] prepMeans ( final Vec [ ] vecs ) { } double [ ] prepMults ( final Vec [ ] vecs ) { } double [ ] [ ] initial_centers ( KMeansModel model , final Vec [ ] vecs , final double [ ] means , final double [ ] mults ) { } private transient int _reinit_attempts ; boolean cleanupBadClusters ( KMeans . Lloyds task , final Vec [ ] vecs , final double [ ] [ ] centers , final double [ ] means , final double [ ] mults ) { } double [ ] [ ] computeStatsFillModel ( KMeans . Lloyds task , KMeansModel model , final Vec [ ] vecs , final double [ ] [ ] centers , final double [ ] means , final double [ ] mults ) { } boolean isDone ( KMeansModel model , double [ ] [ ] newCenters , double [ ] [ ] oldCenters ) { } @ Override protected void compute2 ( ) { } } private static class TotSS extends MRTask < KMeans . TotSS > { double [ ] _means ; double [ ] _mults ; double _tss ; TotSS ( double [ ] means , double [ ] mults ) { } @ Override public void map ( Chunk [ ] cs ) { } @ Override public void reduce ( KMeans . TotSS other ) { } } private static class SumSqr extends MRTask < KMeans . SumSqr > { double [ ] [ ] _centers ; double [ ] _means ; double [ ] _mults ; final int _ncats ; double _sqr ; SumSqr ( double [ ] [ ] centers , double [ ] means , double [ ] mults , int ncats ) { } @ Override public void map ( Chunk [ ] cs ) { } @ Override public void reduce ( KMeans . SumSqr other ) { } } private static class Sampler extends MRTask < KMeans . Sampler > { double [ ] [ ] _centers ; double [ ] _means ; double [ ] _mults ; final int _ncats ; final double _sqr ; final double _probability ; final long _seed ; double [ ] [ ] _sampled ; Sampler ( double [ ] [ ] centers , double [ ] means , double [ ] mults , int ncats , double sqr , double prob , long seed ) { } @ Override public void map ( Chunk [ ] cs ) { } @ Override public void reduce ( KMeans . Sampler other ) { } } private static class Lloyds extends MRTask < KMeans . Lloyds > { double [ ] [ ] _centers ; double [ ] _means ; double [ ] _mults ; final int _ncats ; final int _k ; double [ ] [ ] _cMeans ; long [ ] [ ] [ ] _cats ; double [ ] _cSqr ; long [ ] _size ; long _worst_row ; double _worst_err ; Lloyds ( double [ ] [ ] centers , double [ ] means , double [ ] mults , int ncats , int k ) { } @ Override public void map ( Chunk [ ] cs ) { } @ Override public void reduce ( KMeans . Lloyds mr ) { } } private static final class ClusterDist { int _cluster ; double _dist ; }

Fix:
error ( "_k" , ( ( ( ( "Cannot<seq2seq4repair_space>make<seq2seq4repair_space>" + ( _parms . _k ) ) + "<seq2seq4repair_space>clusters<seq2seq4repair_space>out<seq2seq4repair_space>of<seq2seq4repair_space>" ) + ( _train . numRows ( ) ) ) + "<seq2seq4repair_space>rows" ) ) ;